Mathematical Programming Computation
Description
Mathematical Programming Computation (MPC) publishes original research articles on computational issues in mathematical programming. Articles report on innovative software, comparative tests, modeling environments, libraries of data, and applications. Coverage includes linear programming, convex optimization, nonlinear programming, stochastic and robust optimization, integer programming, combinatorial optimization, network algorithms, and global optimization. A key feature of the journal is the inclusion of accompanying software and data with the research articles. The journal’s review process includes evaluation and testing of accompanying software, aiming at verification of reported computational results. The journal strongly supports the development and distribution of open source software, and archives submitted software with the corresponding research articles.
5 Volumes 15 Issues 54 Articles available from 2009 - 2013
Browse Volumes & IssuesLatest Articles
-
Full Length Paper
TACO: a toolkit for AMPL control optimization
-
Full Length Paper
Parallel stochastic gradient algorithms for large-scale matrix completion
-
Full Length Paper
Efficient block-coordinate descent algorithms for the Group Lasso
Continue reading...
To view the rest of this content please follow the download PDF link above.